An empirical investigation into the capabilities of anomaly detection approaches for test smell detection

被引：0
|
作者：
Pontillo, Valeria [1 ]
Martins, Luana [2 ]
Machado, Ivan [3 ]
Palomba, Fabio [2 ]
Ferrucci, Filomena [2 ]
机构：
[1] Software Languages (SOFT) Lab — Vrije Universiteit Brussel, Belgium
[2] Software Engineering (SeSa) Lab - Department of Computer Science, University of Salerno, Italy
[3] Federal University of Bahia, Salvador, Brazil
来源：
Journal of Systems and Software | / 222卷
关键词：
Number:; -; Acronym:; EC; Sponsor: European Commission; BOL0188/2020; FAPESB; Sponsor: Fundação de Amparo à Pesquisa do Estado da Bahia; PIE0002/2022;
D O I：
112320
中图分类号：
学科分类号：
摘要：
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